Spam Classification Based on E-Mail Path Analysis

Spam Classification Based on E-Mail Path Analysis

Palla Srikanth (University of North Texas, USA), Dantu W. Ram (University of North Texas, USA) and Cangussu João (University of Texas at Dallas, USA)
DOI: 10.4018/978-1-61692-000-5.ch021
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Email spam is the most effective form of online advertising. Unlike telephone marketing, email spamming does not require huge human or financial resources investment. Most existing spam filtering techniques concentrate on the emails’ content. However, most spammers obfuscate their emails’ content to circumvent content-based spam filters. An integrated solution for restricting spam emails is needed as content analyses alone might not provide a solution for filtering unsolicited emails. Here we present a new method for isolating unsolicited emails. Though spammers obfuscate their emails’ content, they do not have access to all the fields in the email header. Our classification method is based on the path an email traverses instead of content. Overall, our classifier produced fewer false positives when compared to current filters such as SpamAssassin. We achieved a precision of 98.65% which compares well with the precisions achieved by SPF, DNSRBL blacklists.

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